I am looking for some reaally basic statistical tools. I have some

sample data, some sample weights for those measurements, and I want to

calculate a mean and a standard error of the mean.

Here are obvious places to look:

numpy

scipy.stats

statsmodels

It seems to me that numpy's "mean" and "average" functions have their

names backwards. That is, often a mean is defined more generally than

average, and includes the possibility of weighting, but in this case

it is "average" that has a weights argument. Can these functions be

merged/renamed/deprecated in the future? It's clear to me that "mean"

should allow for weights.

None of these modules, above, offer standard error of the mean which

incorporates weights. scipy.stats.sem() doesn't, and that's the closest

thing. numpy's "var" doesn't allow weights.

There aren't any weighted variances in the above modules.

Again, are there favoured codes for these functions? Can they be

incorporated appropriately in the future?

Most immediately, I'd love to get code for weighted sem. I'll write it

otherwise, but it might be crude and dumb...

UBC